BAMBO: Construct Ability and Efficiency LLM Pareto Set via Bayesian Adaptive Multi-objective Block-wise Optimization
Published:Dec 10, 2025 15:32
•1 min read
•ArXiv
Analysis
This article introduces BAMBO, a method for optimizing Large Language Models (LLMs) to achieve a Pareto set balancing ability and efficiency. The approach uses Bayesian optimization and block-wise optimization, suggesting a focus on computational efficiency and model performance trade-offs. The source being ArXiv indicates this is a research paper.
Key Takeaways
- •BAMBO is a method for optimizing LLMs.
- •It aims to create a Pareto set balancing ability and efficiency.
- •The method uses Bayesian and block-wise optimization.
- •The paper is a research publication.
Reference
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